TY - JOUR
T1 - Regional International Organizations and Individual Immigration Attitudes
T2 - Results from Finite Mixture Models
AU - Bagozzi, Benjamin E.
AU - Brawner, Thomas
AU - Mukherjee, Bumba
AU - Yadav, Vineeta
PY - 2014/5
Y1 - 2014/5
N2 - When are individuals more likely to support immigration? We suggest here that regional international organizations (IOs; for example, the European Union) publicly release reports about the scale and benefits of immigration to member states in the region in which these IOs operate. We argue that unlike individuals who are uninformed about immigration, informed individuals who have more knowledge of the main regional IO in which their country participates will be more likely to employ immigration reports released by their regional IO to construct their immigration attitudes. They will also perceive that these reports are credible. The credibility of these reports helps individuals with more knowledge about their region's main IO to view immigrants favorably, which translates to support for immigration. We test our prediction by developing a finite mixture model that statistically accounts for the econometric challenges that emerge when uninformed individuals "save face" by disproportionately opting for the middle "status quo" category in ordinal survey response variables of immigration support. Results from the finite mixture model corroborate our prediction and are more reliable than estimates from a standard ordered probit model.
AB - When are individuals more likely to support immigration? We suggest here that regional international organizations (IOs; for example, the European Union) publicly release reports about the scale and benefits of immigration to member states in the region in which these IOs operate. We argue that unlike individuals who are uninformed about immigration, informed individuals who have more knowledge of the main regional IO in which their country participates will be more likely to employ immigration reports released by their regional IO to construct their immigration attitudes. They will also perceive that these reports are credible. The credibility of these reports helps individuals with more knowledge about their region's main IO to view immigrants favorably, which translates to support for immigration. We test our prediction by developing a finite mixture model that statistically accounts for the econometric challenges that emerge when uninformed individuals "save face" by disproportionately opting for the middle "status quo" category in ordinal survey response variables of immigration support. Results from the finite mixture model corroborate our prediction and are more reliable than estimates from a standard ordered probit model.
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U2 - 10.1080/03050629.2014.899226
DO - 10.1080/03050629.2014.899226
M3 - Article
AN - SCOPUS:84902462865
SN - 0305-0629
VL - 40
SP - 350
EP - 375
JO - International Interactions
JF - International Interactions
IS - 3
ER -